Method and Apparatus for Selective Disqualification of Digital Images

ABSTRACT

An unsatisfactory scene is disqualified as an image acquisition control for a camera. An image is acquired. One or more eye regions are determined. The eye regions are analyzed to determine whether they are blinking, and if so, then the scene is disqualified as a candidate for a processed, permanent image while the eye is completing the blinking.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a Continuation of U.S. patent application Ser. No.12/849,597, filed Aug. 3, 2010; which is a Continuation of U.S. patentapplication Ser. No. 11/460,218, filed Jul. 26, 2006, now U.S. Pat. No.7,792,335, which claims priority to U.S. provisional patent applicationNo. 60/776,338, filed Feb. 24, 2006. This application is related to U.S.patent application Ser. No. 11/460,225, filed Jul. 26, 2006, now U.S.Pat. No. 7,804,983; and Ser. No. 11/460,227, filed Jul. 26, 2006, nowU.S. Pat. No. 7,551,754. Each of these applications is herebyincorporated by reference.

1. FIELD OF THE INVENTION

The invention relates to digital image acquisition, and particularly todisqualifying a scene as a candidate for a processed, permanent imagedue to the presence of one or more unsatisfactory features in the image.

2. DESCRIPTION OF THE RELATED ART

Cameras are becoming strong computation tools. In particular,FotoNation, Inc., assignee of the present application, has developedmany advantageous face detection tools. Some of these are described atU.S. patent application Ser. Nos. 10/608,776, 10/608,810, 10/764,339,10/919,226, 11/182,718, and 11/027,001, which are hereby incorporated byreference.

This differs from using a trigger to take a picture. This also differsfrom waiting for an event that may or may not happen (e.g. a smile).U.S. Pat. No. 6,301,440 discloses adjusting image capture parametersbased on analysis of temporary images, and awaiting taking a pictureuntil everyone in the temporary images is smiling. The camera must awaita certain event that may or may not ever happen. It is many times notacceptable to make people wait for the camera to decide that a scene isoptimal before taking a picture, and there is no description in the '440patent that would alleviate such dilemma. The '440 patent also providesno guidance as to how to detect or determine certain features within ascene.

There are also security cameras that take pictures when a subject entersthe view of the camera. These generally detect motion or abrupt changesin what is generally a stagnant scene.

SUMMARY OF THE INVENTION

A method is provided for disqualifying an unsatisfactory scene as animage acquisition control for a camera. An analysis of the content ofthe captured image determines whether the image should be acquired ordiscarded. One example includes human faces. It may be determinedwhether an image is unsatisfactory based on whether the eyes are closed,partially closed or closing down or moving up during a blinking process.Alternatively, other non-desirable or unsatisfactory expressions oractions such as frowning, covering one's face with a hand or otheroccluding or shadowing of a facial feature or other key feature of ascene, or rotating the head away from the camera, etc., may be detected.

A present image of a scene is captured including a face region. One ormore groups of pixels is/are identified corresponding to the region ofinterest, such as an eye region, or a mouth within the face region.

In the case of blink detection, it is determined whether the eye regionis in a blinking process. If so, then the scene is disqualified as acandidate for a processed, permanent image while the eye is completingthe blinking.

The present image may include a preview image, and the disqualifying mayinclude delaying full resolution capture of an image of the scene. Thedelaying may include ending the disqualifying after a predetermined waittime.

A preview image may be used. This can provide an indication of a regionof interest (ROI) where the eyes may be in the captured image. Thisprovides a fast search in the final image of the mouth or eyes based onspatial information provided from the analysis of preview images.

The delaying may include predicting when the blinking will be completedand ending the disqualifying at approximately the predicted blinkcompletion time. The predicting may include determining a point of acomplete blinking process the scene is at, and calculating a remaindertime for completion of the blinking. The calculating may includemultiplying a fraction of the complete blinking process remaining timesa predetermined complete blinking process duration. The predeterminedcomplete blinking process duration may be programmed based on an averageblinking process duration and/or may be determined based on estimating atime from a beginning of the blinking to the present and in view of thefraction representing the point of the complete blinking process thescene is at. The estimating may be based on analyzing a temporal captureparameter of one or more previous preview images relative to that of thepresent preview image. The fraction may be determined based on whetherthe eye that is blinking is opening or closing in the present previewimage, and a degree to which the eye is open or shut.

The method may include determining whether the eye is blinking includingdetermining a degree to which the eye is open or shut. The degree towhich the eye is open or shut may be determined based on relativelyanalyzing the present preview image and one or more other preview imagesrelatively acquired within less than a duration of a complete blinkingprocess. The determining whether the eye is blinking may includedetermining a degree of blurriness of one or both eye lids. It may bedetermined what portion of a pupil, an iris, one or both eye lids or aneye white that is/are showing, or combinations thereof. A color analysisof the eye may be performed and differentiating pixels corresponding toan eye lid tone from pixels corresponding to an iris tone or pupil toneor eye white tone, or combinations thereof. A shape analysis of the eyemay be performed and pixels differentiated as corresponding to an eyelid shape contrast with those corresponding to an iris shape or pupilshape or eye white shape, or combinations thereof.

The present image may include a full resolution capture image. Thedisqualifying may include foregoing further processing of the presentimage. It may be determined whether the eye is blinking includingdetermining a degree to which the eye is open or shut. This may includerelatively analyzing the present preview image and one or more otherpreview images relatively acquired within less than a duration of acomplete blinking process. The determination of whether the eye isblinking may be based on determining a degree of blurriness of one orboth eye lids.

The method may include determining a portion of a pupil, an iris, one orboth eye lids or an eye white that is/are showing, or combinationsthereof. A color analysis of the eye may be performed and pixelsdifferentiated as corresponding to an eye lid tone contrasted withpixels corresponding to an iris tone or pupil tone or eye white tone, orcombinations thereof. A shape analysis of the eye may be performed andpixels differentiated as corresponding to an eye lid shape contrastedwith pixels corresponding to an iris shape or pupil shape or eye whiteshape, or combinations thereof.

The present image may include a full resolution capture image. Themethod may include assembling a combination image including pixels fromthe present image and open-eye pixels corresponding to the eye that isblinking from a different image. The different image may include apreview image or a post-view image or another full resolution image. Thedifferent image may include a lower resolution than the present image,and the assembling may include upsampling the different image ordownsampling the present image, or a combination thereof. The method mayalso include aligning the present image and the different image,including matching an open-eye pixel region to a blinking eye region inthe present image.

The invention may also be implemented to disqualify images out of aselection of images that are part of a stream, such as a video stream.

An eye region may be identified based on identifying a face region, andanalyzing the face region to determine the mouth or eye region therein.

A new image may be captured due to the disqualifying to replace thepresent image.

A pair of images may be captured and analyzed to determine that at leastone of the pair of images includes no blinking.

The interval between multiple captures can be calculated to be longerthan a single blink time.

A warning signal may be provided regarding the blinking so that thephotographer may be aware that she may need to take another picture.

The invention in its various alternatives, may address single ormultiple faces in a single image, such as a group shot. A second eyeregion of another face may be identified within the scene. Additionaleye regions may also be identified within the scene. It may bedetermined whether the second eye region is in a blinking process. Ifso, then the method may include disqualifying the scene as a candidatefor a processed, permanent image while the second eye is completing theblinking. Capturing or further processing may be disqualified for fullresolution images until the eye regions of each face region within thescene include no blinking eyes.

A further method is provided for automatically disqualifying anunsatisfactory scene as an image acquisition control of a camera. Themethod includes acquiring multiple preview images. Information isextracted from the multiple preview images. One or more changes is/areanalyzed in the scene between individual images of the multipletemporary images. Based on the analyzing, it is determined whether oneor more unsatisfactory features exist within the scene. The scene isdisqualified as a candidate for a processed, permanent image while theone or more unsatisfactory features continue to exist.

The analyzing may include identifying one or more groups of pixels thatcorrespond to a facial feature having an unsatisfactory configuration.The one or more groups of pixels may include an eye group, and theunsatisfactory configuration may include a blinking configuration. Theone or more groups of pixels may include a mouth configuration, and theunsatisfactory configuration may include a frowning configuration. Adisqualifying interval may be determined during which no processed,permanent image is to be acquired.

The analyzing may include identifying one or more groups of pixels thatcorrespond to a facial feature having an unsatisfactory configuration.The one or more groups of pixels may include any occlusions such as ahand covering the face or a face that is turned away form the camera.

One or more processor readable storage devices having processor readablecode embodied thereon are also provided. The processor readable code isfor programming one or more processors to perform a method ofdisqualifying an unsatisfactory scene as an image acquisition controlfor a camera, as set forth herein above or below. The processor may beembedded as part of the camera or external to the acquisition device.The acquisition device may be a hand held camera, a stationary camera, avideo camera, a mobile phone equipped with a acquisition device, a handheld device equipped with a acquisition device, a kiosk booth, such asones used for portraits, a dedicated portrait camera such as one usedfor security or identifications or generically, any image capturedevice.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a method for disqualifying a scene that includes ablinking eye in accordance with a preferred embodiment.

FIG. 2 illustrates a method of predicting a blinking completion timeinterval in accordance with a preferred embodiment.

FIG. 3 illustrates a method of determining a degree to which an eye isopen or shut in accordance with a preferred embodiment.

FIG. 4 a illustrates a method of determining whether to forego furtherprocessing of an image in accordance with a preferred embodiment.

FIG. 4 b illustrates a method of assembling a combination image inaccordance with a preferred embodiment.

FIG. 5 illustrates a preferred embodiment of a workflow of correctingimages based on finding eyes in the images.

FIG. 6 a illustrates a generic workflow of utilizing eye information inan image to delay image acquisition in accordance with a preferredembodiment.

FIG. 6 b illustrates a generic workflow of utilizing face information ina single or a plurality of images to adjust the image renderingparameters prior to outputting the image in accordance with a preferredembodiment.

FIGS. 7 a-7 d illustrate face, eye or mouth detection, or combinationsthereof, in accordance with one or more preferred embodiments.

FIG. 8 a illustrates a blink detection and correction method inaccordance with one or more preferred embodiments.

FIG. 8 b describes an illustrative system in accordance with a preferredembodiment to determine whether an eye is blinking in the camera as partof the acquisition process, and whether to capture, discard or store theimage, or whether to substitute an open eye for a blinking eye region.

FIG. 9 illustrate an automatic focusing capability in the camera as partof the acquisition process based on the detection of an eye inaccordance with one or more preferred embodiments.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

Systems and methods are described in accordance with preferred andalternative embodiments. These techniques provide enhanced functionalityand improved usability, as well as avoiding missed shots. With them, adigital camera is able to decide when a subject's facial expression maybe inappropriate, unsatisfactory or non-desirable. One example isblinking, and others include frowning occlusions and shadowing. Thecapture device can either not take the picture, delay the acquisitionfor an appropriate duration, immediately take another picture, warn acamera user, or take steps to enhance the unsatisfactory image later, orcombinations of these or other steps. The camera may delay takinganother picture for a certain amount of time such as roughly 300milliseconds seconds or for an average blinking interval, or until theblinking is determined to be over. The user could be warned beforesnapping a picture or after the picture has been taken that thesubject's eyes may have been closed or semi closed.

A predictive system is provided that disqualifies images if eyes areclosed or partially closed. The system predicts when a picture cannot betaken, i.e., those times when a detected blinking process will beongoing until it is completed. Disqualified images may be alreadycaptured and disqualified only in a post-capture filtering operation,either within the camera or on an external apparatus. The system maytake multiple images to enhance the probability that one or more of theimages will not be disqualified for including one or more blinking eyes.Such system is useful in the case of a group shot where the probabilityof one subject in the process of blinking increases as the number ofsubjects increase. The system, based on the number of faces in theimage, can automatically determine the amount of images to besequentially taken to provide a probability that at least one of theimages will have no blinking eyes that is above a threshold amount,e.g., 50%, 60%, 67%, 70%, 75%, 80%, 90% or 95%.

An image may be generated as a combination of a present image, and apreview, post-view or other full resolution image. For example, thecombination image may include a face region and some background imagery,wherein one or both eye regions, which are unsatisfactorily closed orpartially closed in the present image, are replaced with one or bothopen eyes from the preview, post-view or other full resolution image.This feature may be combined with features presented in U.S. patentapplication Ser. No. 10/608,776, which is assigned to the same assigneeas the present application and is hereby incorporated by reference. Inthe '776 application, a method of digital image processing using facedetection is described. A group of pixels is identified that correspondsto a face within a digital image. A second group of pixels is identifiedthat corresponds to another feature within the digital image. Are-compositioned image is determined including a new group of pixels forat least one of the face and the other feature.

The embodiments herein generally refer to a single face within a digitalimage or scene (e.g., prior to image capture or that may have alreadybeen digitally captured), and generally to “an eye”. However, thesedescriptions can extended to both eyes on a single face, and to morethan a single face (group shot), and the camera can disqualify the sceneif a certain number of one or two, three, four or more eyes aredetermined to be blinking. The camera is able to perform thedisqualifying and/or other operations, as described herein or otherwise,until a high percentage or all of the subjects have one or both of theireyes open.

In one embodiment, the camera will take the picture right after thesubject completes a blinking process. The present system can be used todisqualify an image having a subject whose eyes are closed, and can takemultiple images to prevent having no images that lack blinking. One ofthe images will likely have eyes open for each subject person, and thepictures can have a mixture of pixels combined into a single image withno eyes blinking. The camera may decide on the number of images to takebased on the number of subjects in the image. The more people, thehigher the likelihood of one person blinking, thus more images should beacquired. If it is acceptable for efficiency that a certain percentageof persons may be blinking in a large group shot, e.g., that is below acertain amount, e.g., 5%, then the number of images can be reduced.These threshold numbers and percentage tolerances can be selected by acamera product manufacturer, program developer, or user of a digitalimage acquisition apparatus. This information may be generated based onanalysis of preview images. The preview image may also assist indetermining the location of the eyes, so that the post processinganalysis can be faster honing into the region of interest as determinedby the preview analysis.

The present system sets a condition under which a picture will not betaken or will not be used or further processed after it has already beentaken, and/or where an additional image or images will be taken toreplace the unsatisfactory image. Thus, another advantageous feature ofa system in accordance with a preferred embodiment is that it cancorrect an acquired blink region with a user's eye information from apreview or post-view image or another full resolution image. The presentsystem preferably uses preview images, which generally have lowerresolution and may be processed more quickly. The present system canalso look for comparison of changes in facial features (e.g., of theeyes or mouth), between images as potentially triggering a disqualifyingof a scene for an image capture. In such a case, the system maydistinguish between a squint which is somewhat permanent or of longerduration during the session than a blink which is more a temporarystate. The system may also through a comparison of multiple imagesdetermine the difference between eyes that are naturally narrow due tothe location of the upper-eye-lid or the epicanthal fold, or based on adetermined nationality of a subject person, e.g., distinguishing Asianfrom Caucasian eyes.

The description herein generally refers to handling a scene wherein anobject person is blinking his or her eyes. However, the invention may beapplied to other features, e.g., when a person is frowning, or when aperson is unsatisfactorily gesturing, talking, eating, having bad hair,or otherwise disposed, or when another person is putting bunny ears onsomeone, or an animal or other person unexpectedly crosses between thecamera and human subject, or the light changes unexpectedly, or the windblows, or otherwise. One or more or all of these disqualifyingcircumstances may be manually set and/or overridden.

FIG. 1 illustrates a method for disqualifying a scene that includes ablinking eye in accordance with a preferred embodiment. A present imageof a scene including a face region is acquired at 110. Optionally, theface region is identified at 120, and the face region analyzed todetermine one or both eye regions therein. One or more groups of pixelscorresponding to an eye region within the face region are identified at130. It is determined whether the eye region is in a blinking process at140. If the eye is determined to be in a blinking process at 140, thenthe scene is disqualified as a candidate for a processed, permanentimage at 150. At this point, the process can simply stop or start againfrom the beginning, or a new image may be captured due to thedisqualifying in order to replace the present image at 160. A warningsignal may be provided regarding the blinking at 170. Full resolutioncapture of an image of the scene may be delayed at 180. As illustratedat FIGS. 4A and 4B, further processing of a present image may be stoppedor a combination image may be assembled as a way of enhancing thedisqualified image.

FIG. 2 illustrates a method of predicting a blinking completion timeinterval in accordance with a preferred embodiment. It is predicted whenthe a blinking process will be completed at 210, and the disqualifyinginterval will end at the predicted blinking completion time. Theinterval may be set at a predetermined wait time 220. This may be setfrom a knowledge of an average blink of one quarter of a second or 250milliseconds, or in a range from approximately 200-400 milli-seconds, orto 0.6, 0.8 or 1.0 seconds, however setting the wait time too long toensure the blinking is complete disadvantageously permits a second blinkto begin or simply makes everyone involved in taking the picture have towait to too long for the disqualifying period to end. A more precisedetermination of the end of the blinking process is desired.

A point of a complete blinking process where a scene is at may bedetermined at 230 of FIG. 2, and then a remainder time can be calculatedfor completion of the blinking. For example, it may be determined thatthe blinking process observed is half way complete. In this example, thedetermined fraction is half or 0.5. This fraction can be advantageouslymultiplied times a predetermined complete blinking process duration at240, e.g., 0.25 seconds, to get a completion time remaining of 0.125.With this more precise determination, there need not be excessive waittime for the disqualifying period to end, while still ensuring that theblinking is over before snapping the picture. Alternative, if multiplepicture have been taken and the blinking is discovered in post-captureprocessing, then a more precise determination of which images will bedisqualified can be determined based on known image capture times.

Various options are provided at FIG. 2 and FIG. 3 for inclusion in theprocess. At 250, a complete blinking process duration based on anaverage blinking process duration is programmed into the camera or otherpre-capture or post-capture processing apparatus. At 240, a completeblinking process duration is determined based on estimating a time froma beginning of the blinking to present, and in view of the determinedfraction. For example, if the determined fraction is one third, and thetime from the beginning of the blinking to present is determined to be0.09 seconds, the complete blink time estimated to be 0.27 seconds, ofwhich 0.18 second remain. At 280, the estimation may be based onanalyzing a temporal capture parameter of one of more previous previewimages relative to that of the present image. For example, if a previouspreview image shows a start of the blinking process, and the cameraknows that the previous preview image was captured 0.08 seconds earlier,and the fraction is one third, then the blinking process may bepredicted to end after another 0.16 seconds. At 270, the fraction isdetermined, including determining whether the blinking eye is opening orclosing, and further determining a degree to which the eye is open orshut.

The determining a degree to which an eye may be open or shut is furtherprovided at 310 of FIG. 3. To do this, the present image is preferablyanalyzed at 320 relative to one or more other preview images acquiredwithin less than a duration of a complete blinking process. An optionaldetermination of a degree of blurriness at 330 of one or both eye lidsmay facilitate a determination of blink speed. A portion of a pupil,iris, one or both eye lids or an eye white that is/are showing may bedetermined at 340 to facilitate determining how open or shut theblinking eye is. Color analysis 350 and shape analysis 360 may also beperformed to differentiate pixels corresponding to features of open eyessuch as a pupil, an iris and/or an eye white, from pixels correspondingto features of shut eyes, or eye lids that would appear in an eye regionof a present scene.

FIG. 4 a illustrates a method of determining whether to forego furtherprocessing of an image 410 in accordance with a preferred embodiment. Inthis case, determining a degree to which the eye is open or shut 420 isperformed for a different purpose than to compute a blinking processcompletion time. In this embodiment, a threshold degree of closure of aneye may be preset, e.g., such that when an image is analyzed accordingto 420, 430, 440, 450, 460, or 470, or combinations thereof, similar toany or a combination of 310-360 of FIG. 3, then if the eye is shut to atleast the threshold degree or greater, then the scene is disqualified,because the eye is too far shut. This can correspond to a situationwherein an eye is not blinking, or where an eye is at the very start orvery end of a blinking process, such that the degree to which the eye isopen is sufficient for keeping the image.

FIG. 4 b illustrates a method of assembling a combination image inaccordance with a preferred embodiment. At 480, a combination image isassembled including pixels from a present image and open eye pixels froma different image that correspond to the eye that is blinking in thepresent image. The different image may be a preview or postview image490. In this case, particularly if the preview or postview image haslower resolution than the present image, then at 500 the preview imagemay be upsampled or the postview image may be downsampled, or acombination thereof. The present image and the different image arepreferably aligned at 510 to match the open eye pixel region in thepreview of postview image to the blinking eye region in the presentimage.

FIG. 5 illustrates further embodiments. If one or more eyes aredetermined to be blinking in an image, then that image is preferablydisqualified from being further processed in accordance with thefollowing. Alternatively, the blinking determination 140 may beperformed somewhere along the way, such as illustrated as an example inFIG. 5. An image may be opened by the application in block 1102. Thesoftware then determines whether eyes or faces, or both, are in thepicture as described in block 1106. If no eyes or faces are detected,the software ceases to operate on the image and exits 1110. In whatfollows, only eyes will be typically referred to for efficiency, buteither faces or eyes or both, or even another facial feature or othernon-facial predetermined scene feature, may be the object of particularoperations (see FIGS. 1, 110, 120 and 130 and U.S. application Ser. No.10/608,776, which is incorporated by reference).

The software may also offer a manual mode, where the user, in block 1116may inform the software of the existence of eyes, and manually marksthem in block 1118. The manual selection may be activated automaticallyif no eyes are found, 1116, or it may even be optionally activated afterthe automatic stage to let the user, via some user interface to eitheradd more eyes to the automatic selection 1112 or even 1114, removeregions that are mistakenly 1110 identified by the automatic process1118 as eyes. Additionally, the user may manually select an option thatinvokes the process as defined in 1106. This option is useful for caseswhere the user may manually decide that the image can be enhanced orcorrected based on the detection of the eyes. Various ways that the eyesmay be marked, whether automatically of manually, whether in the cameraor by the applications, and whether the command to seek the eyes in theimage is done manually or automatically, are all included in preferredembodiments herein. In a preferred embodiment, faces are first detected,and then eyes are detected within the faces.

In an alternative embodiment, the eye detection software may beactivated inside the camera as part of the acquisition process, asdescribed in Block 1104. In this scenario, the eye detection portion1106 may be implemented differently to support real time or near realtime operation. Such implementation may include sub-sampling of theimage, and weighted sampling to reduce the number of pixels on which thecomputations are performed. This embodiment is further described withreference to FIG. 6 a.

In an alternative embodiment, the eye detection can then also make useof information provided from preview images to determine the location ofthe eyes in preview, thus expediting the analysis being performed in asmaller region on the final image.

In an alternative embodiment, the eye detection software may beactivated inside the rendering device as part of the output process, asdescribed in Block 1103. In this scenario, the eye detection portion1106 may be implemented either within the rendering device, using thecaptured image or using a single or plurality of preview images, orwithin an external driver to such device. This embodiment is furtherdescribed with reference to FIG. 6 b.

After the eyes and/or faces or other features are tagged, or marked,whether manually as defined in 1118, or automatically 1106, the softwareis ready to operate on the image based on the information generated bythe eye-detection, face detection, or other feature-detection stage. Thetools can be implemented as part of the acquisition, as part of thepost-processing, or both. As previously averred to, blink determinationmay be performed at this point at 140 (see FIGS. 1-4 b and above). Theimage may be disqualified at 1119 if blinking is found, such thatfurther processing, as known to one familiar in the art of digitalphotography is efficiently foregone.

Referring to FIG. 6 a, which describes a process of using face detectionto improve in camera acquisition parameters, as aforementioned in FIG.5, block 1106. In this scenario, a camera is activated at 1000, forexample by means of half pressing the shutter, turning on the camera,etc. The camera then goes through the normal pre-acquisition stage todetermine at 1004 the correct acquisition parameters such as aperture,shutter speed, flash power, gain, color balance, white point, or focus.In addition, a default set of image attributes, particularly related topotential faces in the image, are loaded at 1002. Such attributes can bethe overall color balance, exposure, contrast, orientation etc.Alternatively, at 1003, a collection of preview images may be analyzedto determine the potential existence of faces in the picture at 1006. Aregion wherein potentially the eyes will be when the full resolution iscaptured may also be predicted at 1008. This alternative technique mayinclude moving on to block 1010 and/or 1002.

An image is digitally captured onto the sensor at 1010. Such action maybe continuously updated, and may or may not include saving such capturedimage into permanent storage.

An image-detection process, preferably a face detection process, asknown to one familiar in the art of image classification and facedetection in particular, is applied to the captured image to seek eyesor faces or other features in the image at 1020. Such face detectiontechniques, include, but are not limited to: knowledge-based;feature-invariant; template-matching; appearance-based; color or motioncues; adaboost-based face detector, Viola-Jones, etc.

If no faces are found, the process terminates at 1032. Alternatively, orin addition to the automatic detection of 1030, the user can manuallyselect, 1034 detected eyes or faces, using some interactive userinterface mechanism, by utilizing, for example, a camera display.Alternatively, the process can be implemented without a visual userinterface by changing the sensitivity or threshold of the detectionprocess. Alternatively, this data may be available form a pre-captureprocess 1003.

When eyes or faces are detected, 1040, they are marked, and labeled.Detecting defined in 1040 may be more than a binary process of selectingwhether an eye or a face is detected or not, it may also be designed aspart of a process where each of the eyes or faces is given a weightbased on size of the eyes or faces, location within the frame, otherparameters described herein, which define the importance of the eye orface in relation to other eyes or faces detected.

Alternatively, or in addition, the user can manually deselect regions1044 that were wrongly false detected as eyes or faces. Such selectioncan be due to the fact that an eye or a face was false detected or whenthe photographer may wish to concentrate on one of the eyes or faces asthe main subject matter and not on other eyes or faces. Alternatively,1046 the user may re-select, or emphasize one or more eyes or faces toindicate that these eyes or faces have a higher importance in thecalculation relative to other eyes or faces. This process as defined in1046 further defines the preferred identification process to be acontinuous value one as opposed to a binary one. The process can be doneutilizing a visual user interface or by adjusting the sensitivity of thedetection process.

After the eyes or faces or other features are correctly isolated at 1040their attributes are compared at 1050 to default values that werepredefined in 1002. Such comparison will determine a potentialtransformation between the two images, in order to reach the samevalues. The transformation is then translated to the camera captureparameters 1070 and the image is acquired 1090.

A practical example is that if the captured face is too dark, theacquisition parameters may change to allow a longer exposure, or openthe aperture. Note that the image attributes are not necessarily onlyrelated to the face regions but can also be in relations to the overallexposure. As an exemplification, if the overall exposure is correct butthe faces are underexposed, the camera may shift into a fill-flash mode.

At 1060, capture is delayed until detected image attributes matchdefault image attributes. An example in accordance with a preferredembodiment is to delay capture until eyes that are blinking and causingthe delay are no longer blinking. At 1070, manual override instructionsmay be entered to take the picture anyway, or to keep a picture or tocontinue processing of a picture, even though blinking is detectedwithin the picture. The picture is taken at 1090, or in accordance withanother embodiment, the picture is stored in full resolution.

Referring to FIG. 6 b, a process is described for using eye, face orother feature detection to improve output or rendering parameters, asaforementioned in FIG. 5, block 1103. In this scenario, a renderingdevice such as a printer or a display, hereinafter referred to as “thedevice” is activated at 2100. Such activation can be performed forexample within a printer, or alternatively within a device connected tothe printer such as a PC or a camera. The device then goes through anormal pre-rendering stage to determine at 2104, the correct renderingparameters such as tone reproduction, color transformation profiles,gain, color balance, white point and resolution. In addition, a defaultset of image attributes, particularly related to potential eyes or facesin the image, are loaded at 2102. Such attributes can be the overallcolor balance, exposure, contrast, or orientation, or combinationsthereof.

An image is then digitally downloaded onto the device 2110. Animage-detection process, preferably an eye or a face detection process,is applied to the downloaded image to seek eyes or faces in the image at2120. If no images are found, the process terminates at 2132 and thedevice resumes its normal rendering process. Alternatively, or inaddition to the automatic detection of 2130, the user can manuallyselect 2134 detected eyes or faces or other features, using someinteractive user interface mechanism, by utilizing, for example, adisplay on the device. Alternatively, the process can be implementedwithout a visual user interface by changing the sensitivity or thresholdof the detection process.

When eyes or faces are detected at 2130, they are marked at 2140, andlabeled. Detecting in 2130 may be more than a binary process ofselecting whether an eye or a face is detected or not. It may also bedesigned as part of a process where each of the eyes or faces is given aweight based on size of the faces, location within the frame, otherparameters described herein, etc., which define the importance of theeye or face in relation to other eyes or faces detected.

Alternatively, or in addition, the user can manually deselect regions at2144 that were wrongly false detected as eyes or faces. Such selectioncan be due to the fact that an eye or face was false detected or whenthe photographer may wish to concentrate on one or two of the eyes orone of the faces as the main subject matter and not on other eyes orfaces. Alternatively, 2146, the user may re-select, or emphasize one ormore eyes or faces to indicate that these eyes or faces have a higherimportance in the calculation relative to other eyes or faces. Thisprocess as defined in 1146, further defines the preferred identificationprocess to be a continuous value one as opposed to a binary one. Theprocess can be done utilizing a visual user interface or by adjustingthe sensitivity of the detection process.

After the eyes or faces or other scene or image features are correctlyisolated at 2140, their attributes are compared at 2150 to defaultvalues that were predefined in 2102. At least one preferred attributethat the process is looking for is blinking eyes. Such comparison willdetermine a potential transformation between the two images, in order toreach the same values. The image may be disqualified at 2160 if one ormore eyes are determined to be blinking. The disqualifying may beoverridden manually at 2170 or open eye pixels may be substituted from adifferent image. The transformation may be translated to the devicerendering parameters, and the image at 2190 may be rendered. The processmay include a plurality of images. In this case at 2180, the processrepeats itself for each image prior to performing the rendering process.A practical example is the creation of a thumbnail or contact sheetwhich is a collection of low resolution images, on a single displayinstance.

A practical example is that if the eyes or face were too darklycaptured, the rendering parameters may change the tone reproductioncurve to lighten the eyes or face. Note that the image attributes arenot necessarily only related to the eye or face regions, but can also bein relation to an overall tone reproduction.

Referring to FIGS. 7 a-7 d, which describe automatic rotation of animage based on the location and orientation of eyes, faces, other facefeatures, or other non-facial features, as highlighted in FIG. 5 atBlock 1130. An image of two faces is provided in FIG. 7 a. Note that thefaces may not be identically oriented, and that the faces may beoccluding. In this case, both eyes are showing on each face, but onlyone eye might be showing.

The software in the eye or face detection stage, including thefunctionality of FIG. 5, blocks 1108 and 1118, will mark the two facesor the four eyes of the mother and son, e.g., the faces may be marked asestimations of ellipses 2100 and 2200, respectively. Using knownmathematical means, such as the covariance matrices of the ellipses, thesoftware will determine the main axes of the two faces 2120 and 2220,respectively as well as the secondary axis 2140 and 2240. Even at thisstage, by merely comparing the sizes of the axes, the software mayassume that the image is oriented 90 degrees, in the case that thecamera is in landscape mode, which is horizontal, or in portrait modewhich is vertical or +90 degrees, aka clockwise, or −90 degrees akacounter clockwise. Alternatively, the application may also be utilizedfor any arbitrary rotation value. However, this information may notsuffice to decide whether the image is rotated clockwise orcounter-clockwise.

FIG. 7 c describes the step of extracting the pertinent features of aface, which are usually highly detectable. Such objects may include theeyes, 2140, 2160 and 2240, 2260, and the lips, 2180 and 2280, or thenose, eye brows, eye lids, features of the eyes, hair, forehead, chin,ears, etc. The combination of the two eyes and the center of the lipscreates a triangle 2300 which can be detected not only to determine theorientation of the face but also the rotation of the face relative to afacial shot. Note that there are other highly detectable portions of theimage which can be labeled and used for orientation detection, such asthe nostrils, the eyebrows, the hair line, nose bridge and the neck asthe physical extension of the face, etc. In this figure, the eyes andlips are provided as an example of such facial features Based on thelocation of the eyes, if found, and the mouth, the image might ought tobe rotated in a counter clockwise direction.

Note that it may not be enough to just locate the different facialfeatures, but such features may be compared to each other. For example,the color of the eyes may be compared to ensure that the pair of eyesoriginated from the same person. Alternatively, the features of the facemay be compared with preview images. Such usage may prevent a case wherea double upper eyelid may be mistaken to a semi closed eye. Anotherexample is that in FIGS. 7 c and 7 d, if the software combined the mouthof 2180 with the eyes of 2260, 2240, the orientation would have beendetermined as clockwise. In this case, the software detects the correctorientation by comparing the relative size of the mouth and the eyes.The above method describes exemplary and illustrative techniques fordetermining the orientation of the image based on the relative locationof the different facial objects. For example, it may be desired that thetwo eyes should be horizontally situated, the nose line perpendicular tothe eyes, the mouth under the nose etc. Alternatively, orientation maybe determined based on the geometry of the facial components themselves.For example, it may be desired that the eyes are elongated horizontally,which means that when fitting an ellipse on the eye, such as describedin blocs 2140 and 2160, it may be desired that the main axis should behorizontal. Similar with the lips which when fitted to an ellipse themain axis should be horizontal. Alternatively, the region around theface may also be considered. In particular, the neck and shoulders whichare the only contiguous skin tone connected to the head can be anindication of the orientation and detection of the face.

A process for determining the orientation of images can be implementedin a preferred embodiment as part of a digital display device.Alternatively, this process can be implemented as part of a digitalprinting device, or within a digital acquisition device.

A process can also be implemented as part of a display of multipleimages on the same page or screen such as in the display of acontact-sheet or a thumbnail view of images. In this case, the user mayapprove or reject the proposed orientation of the images individually orby selecting multiple images at once. In the case of a sequence ofimages, the orientation of images may be determined based on theinformation as approved by the user regarding previous images.

Alternatively, as described by the flow chart of FIG. 8 a, a similarmethod may be utilized in the pre-acquisition stage, to determine ifdigital simulation or re-compositioning of an image with open eyes maybe advantageous or not, e.g., when an eye is determined to be blinkingU.S. Pat. No. 6,151,073 to Steinberg et al. is hereby incorporated byreference. In block 1108 of FIG. 5, the camera searched for theexistence of eyes or faces in the image. At 1460, it is determinedwhether one or more eyes were founding the image. If not, then exit at1462. If so, then the eyes are marked at 1464. The eye regions areanalyzed at 1470. If the eyes are determined to be sufficiently open at1474, then the image is left as is at 1478. However, if the eyes are notdetermined to be sufficiently open, or are closed beyond a thresholdamount, then the process can proceed to correction at 1480, 1490 and/or1494. At 1480, a sub-routine for digitally simulating open eyes isprovided. A mask or masks define selected regions, i.e., in thisexample, eye regions. The exposure may be increased at 1484 or that maybe skipped. Shape and/or color processing is performed at 1486 to theselected eye regions. For example, where closed eye lids exist in theoriginal image, pupil, iris and eye white shapes and colors are providedbetween open eye lids to be substituted over the closed eye lids. Tonereproduction is provided at 1488.

At 1490, single or multiple results may be provided to a user. The usermay select a preferred result at 1492, and the correction is applied at1498. Alternatively, the image may be displayed at 1494 to the user witha parameter to be modified such as iris color or pupil shape. The userthen adjusts the extent of the modification at 1496, and the image iscorrected at 1498.

FIG. 8 b provides another workflow wherein picture taking mode isinitiated at 1104 as in FIG. 5. The image is analyzed at 4820. Adetermination of whether eyes were found in the image is made at 1106.If not, then exit at 1110. If so, then the eyes are marked at 1108. Theeye regions are analyzed at 4840, and if the eyes are open 4960, thenthe picture is either taken, stored (e.g., if the picture was previouslytaken) or taken and stored at 4880. If the eyes are determined to beclosed at 4860, e.g., because blinking is taking place, then the imagemay be discarded or image capture delayed at 4980, or alternatively thepicture may be taken at 4900. In this latter embodiment, open eyesregions are substituted for pixels of the blinking eyes at 4920, and thecombination picture is stored at 4940.

FIG. 9 illustrates a technique involving motion of eye lids. A focusingmechanism is activated at 1170. The camera seeks the eyes at 1750. Ifeyes are not detected at 1760, then spatial based auto-focusingtechniques may be performed at 1762. If eyes are detected, then regionsare marked at 1770. The regions are displayed at 1772. The user may takethe picture now at 1790. However, the user may move to focus trackingmode at 1780. While the eye lids are moving, e.g., during a blinkingprocess 1782, the eye lid movement is tracked at 1784. A delay or scenedisqualification is imposed while the eye lids are moving during theblinking process at 1786. When the disqualifying period ends, the usermay take the picture, or the camera may be programmed to automaticallytake the shot at 1790.

What follows is a cite list of references which are, in addition to thatwhich is described as background, the invention summary, the abstract,the brief description of the drawings and the drawings, and otherreferences cited above, hereby incorporated by reference into thedetailed description of the preferred embodiments as disclosingalternative embodiments:

U.S. Pat. Nos. 6,965,684, 6,301,440, RE33682, RE31370, U.S. Pat. Nos.4,047,187, 4,317,991, 4,367,027, 4,638,364, 5,291,234, 5,488,429,5,638,136, 5,710,833, 5,724,456, 5,781,650, 5,812,193, 5,818,975,5,835,616, 5,870,138, 5,978,519, 5,991,456, 6,097,470, 6,101,271,6,128,397, 6,148,092, 6,151,073, 6,188,777, 6,192,149, 6,249,315,6,263,113, 6,268,939, 6,282,317, 6,301,370, 6,332,033, 6,393,148,6,404,900, 6,407,777, 6,421,468, 6,438,264, 6,456,732, 6,459,436,6,473,199, 6,501,857, 6,504,942, 6,504,951, 6,516,154, and 6,526,161;

United States published patent applications no. 2003/0071908,2003/0052991, 2003/0025812, 2002/0172419, 2002/0114535, 2002/0105662,and 2001/0031142;

U.S. provisional application No. 60/776,338, entitled Human EyeDetector;

Japanese patent application no. JP5260360A2;

British patent application no. GB0031423.7;

Yang et al., IEEE Transactions on Pattern Analysis and MachineIntelligence, Vol. 24, no. 1, pp 34-58 (January 2002); and

Baluja & Rowley, “Neural Network-Based Face Detection,” IEEETransactions on Pattern Analysis and Machine Intelligence, Vol. 20, No.1, pages 23-28, January 1998.

While an exemplary drawings and specific embodiments of the presentinvention have been described and illustrated, it is to be understoodthat the scope of the present invention is not to be limited to theparticular embodiments discussed. Thus, the embodiments shall beregarded as illustrative rather than restrictive, and it should beunderstood that variations may be made in those embodiments by workersskilled in the arts without departing from the scope of the presentinvention as set forth in the claims that follow and their structuraland functional equivalents.

In addition, in methods that may be performed according to the claimsbelow and/or preferred embodiments herein, the operations have beendescribed in selected typographical sequences. However, the sequenceshave been selected and so ordered for typographical convenience and arenot intended to imply any particular order for performing theoperations, unless a particular ordering is expressly provided orunderstood by those skilled in the art as being necessary.

1. A method of selectively disqualifying a scene as a candidate forpermanent capture, storage or processing, or combinations thereof, themethod comprising: identifying a key feature within a scene in apreacquisition stage, in a video stream or within a collection ofpreview images, or combinations thereof; determining that an occludingobject is currently occluding a significant portion of the key feature;rejecting the scene as a candidate for digital image capture due to theoccluding; performing one or both of shape analysis and temporalanalysis of movement of the occluding object relative to the keyfeature; and automatically acquiring a digital image after delaying fora period of time, wherein the delaying of said acquiring the new imagecorresponds to an estimated time for said occluding of said key featureto end based on said one or both of shape analysis and temporal analysisof movement.
 2. The method of claim 1, wherein the identifying comprisesacquiring the scene within a collection of preview images.
 3. The methodof claim 1, wherein the one or both of shape analysis and temporalanalysis comprises determining a speed at which the occluding object ismoving into or out of the scene.
 4. The method of claim 1, wherein theone or both of shape analysis and temporal analysis comprisesdetermining a speed of the occluding object for determining when theoccluding will end.
 5. The method of claim 1, wherein the one or both ofshape analysis and temporal analysis comprises a speed and a directionof the movement of the occluding object.
 6. The method of claim 1,further comprising determining an extent to which the key feature isshowing.
 7. The method of claim 6, further comprising determiningwhether the key feature is currently being covered or uncovered.
 8. Themethod of claim 1, wherein the key feature comprises a face, eye ormouth region, or combinations thereof.
 9. The method of claim 1, whereinthe performing one or both of shape analysis and temporal analysis ofmovement comprises determining a direction of movement of the occludingobject.
 10. The method of claim 1, wherein the performing one or both ofshape analysis and temporal analysis comprises determining a degree ofblurriness of the occluding object due to object movement duringexposure.
 11. One or more non-transitory computer readable media havingcode embedded therein for programming a processor to perform a method ofselectively disqualifying a scene as a candidate for permanent capture,storage or processing, or combinations thereof, the method comprising:identifying a key feature within a scene in a preacquisition stage, in avideo stream or within a collection of preview images, or combinationsthereof; determining that an occluding object is currently occluding asignificant portion of the key feature; rejecting the scene as acandidate for digital image capture due to the occluding; performing oneor both of shape analysis and temporal analysis of movement of theoccluding object relative to the key feature; and automaticallyacquiring a digital image after delaying for a period of time, whereinthe delaying of said acquiring the digital image corresponds to anestimated time for said occluding of said key feature to end based onsaid one or both of shape analysis and temporal analysis of movement.12. The one or more computer readable media of claim 11, wherein theidentifying comprises acquiring a collection of preview images.
 13. Theone or more computer readable media of claim 11, wherein the one or bothof shape analysis and temporal analysis comprises determining a speed atwhich the occluding object is moving into or out of the scene.
 14. Theone or more computer readable media of claim 11, wherein the one or bothof shape analysis and temporal analysis comprises determining a speed ofthe occluding object for determining when the occluding will end. 15.The one or more computer readable media of claim 11, wherein the one orboth of shape analysis and temporal analysis comprises a speed and adirection of the movement of the occluding object.
 16. The one or morecomputer readable media of claim 11, wherein the method furthercomprises determining an extent to which the key feature is showing. 17.The one or more computer readable media of claim 16, wherein the methodfurther comprises determining whether the key feature is currently beingcovered or uncovered.
 18. The one or more computer readable media ofclaim 11, wherein the key feature comprises a face, eye or mouth region,or combinations thereof.
 19. The one or more computer readable media ofclaim 11, wherein the performing one or both of shape analysis andtemporal analysis of movement comprises determining a direction ofmovement of the occluding object.
 20. The one or more computer readablemedia of claim 11, wherein the performing one or both of shape analysisand temporal analysis comprises determining a degree of blurriness ofthe occluding object due to object movement during exposure.
 21. Adigital image acquisition device, comprising: a lens and image sensorfor acquiring digital images; a processor; and one or more computerreadable media having code embedded therein for programming a processorto perform a method of selectively disqualifying a scene as a candidatefor permanent capture, storage or processing, or combinations thereof,wherein the method comprises: identifying a key feature within a scenein a preacquisition stage, in a video stream or within a collection ofpreview images, or combinations thereof; determining that an occludingobject is currently occluding a significant portion of the key feature;rejecting the scene as a candidate for digital image capture due to theoccluding; performing one or both of shape analysis and temporalanalysis of movement of the occluding object relative to the keyfeature; and automatically acquiring a digital image to replace thepresent image after delaying for a period of time, wherein the delayingof said acquiring the digital image corresponds to an estimated time forsaid occluding of said key feature to end based on said one or both ofshape analysis and temporal analysis of movement.
 22. The digital imageacquisition device of claim 21, wherein the identifying comprisesacquiring a collection of preview images.
 23. The digital imageacquisition device of claim 21, wherein the one or both of shapeanalysis and temporal analysis comprises determining a speed at whichthe occluding object is moving into or out of the scene.
 24. The digitalimage acquisition device of claim 21, wherein the one or both of shapeanalysis and temporal analysis comprises determining a speed of theoccluding object for determining when the occluding will end.
 25. Thedigital image acquisition device of claim 21, wherein the one or both ofshape analysis and temporal analysis comprises a speed and a directionof the movement of the occluding object.
 26. The digital imageacquisition device of claim 21, wherein the method further comprisesdetermining an extent to which the key feature is showing.
 27. Thedigital image acquisition device of claim 26, wherein the method furthercomprises determining whether the key feature is currently being coveredor uncovered.
 28. The digital image acquisition device of claim 21,wherein the key feature comprises a face, eye or mouth region, orcombinations thereof.
 29. The digital image acquisition device of claim21, wherein the performing one or both of shape analysis and temporalanalysis of movement comprises determining a direction of movement ofthe occluding object.
 30. The digital image acquisition device of claim21, wherein the performing one or both of shape analysis and temporalanalysis comprises determining a degree of blurriness of the occludingobject due to object movement during exposure.